Predictive condition monitoring and predictive maintenance represent a revolution in the management of infrastructure and transport vehicles. These technologies use advanced sensors and machine learning algorithms to monitor the condition of vehicles and machinery in real time, predict potential failures, and schedule maintenance before serious problems occur.

Predictive maintenance relies on the continuous analysis of data collected from sensors installed on various vehicle components, such as engines, brakes, and suspension systems. This data is analyzed to identify patterns that indicate wear or anomalies. By predicting failures before they happen, transport companies can reduce vehicle downtime, minimize repair costs, and improve overall safety. Additionally, the ability to maintain vehicles in optimal condition extends their lifespan and enhances the quality of service offered to passengers.